{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Split data\n",
    "divide the data into sleep part and awake part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Import finished!\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "import datetime\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sb\n",
    "from scipy.signal import argrelextrema\n",
    "\n",
    "print (\"Import finished!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## define some functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sizeof_fmt(num, suffix='B'):\n",
    "    '''output data sizes in a nice way, i.e. B, KiB, MiB, GiB, ...\n",
    "    by Fred Cirera,  https://stackoverflow.com/a/1094933/1870254,\n",
    "    modified'''\n",
    "    for unit in ['', 'Ki', 'Mi', 'Gi', 'Ti', 'Pi', 'Ei', 'Zi']:\n",
    "        if abs(num) < 1024.0:\n",
    "            return \"%3.1f %s%s\" % (num, unit, suffix)\n",
    "        num /= 1024.0\n",
    "    return \"%.1f %s%s\" % (num, 'Yi', suffix)\n",
    "\n",
    "def readMiceData(batch, name):\n",
    "    if debug:\n",
    "        print('{}/batch{}/{}.Activity.txt'.format(path, batch, name))\n",
    "        print('{}/batch{}/{}.Temperature.txt'.format(path, batch, name))\n",
    "    a = np.genfromtxt('{}/batch{}/{}.Activity.txt'.format(path, batch, name))\n",
    "    b = np.genfromtxt('{}/batch{}/{}.Temperature.txt'.format(path, batch, name))\n",
    "\n",
    "    if a[0,0] != b[0,0]:\n",
    "        start = max(a[0,0], b[0,0])\n",
    "    else:\n",
    "        start = a[0,0]\n",
    "    if a[-1,0] != b[-1,0]:\n",
    "        end = min(a[-1,0], b[-1,0])\n",
    "    else:\n",
    "        end = a[-1,0]\n",
    "\n",
    "    a = a[(a[:,0]<=end)]\n",
    "    a = a[(a[:,0]>=start)]\n",
    "    b = b[(b[:,0]<=end)]\n",
    "    b = b[(b[:,0]>=start)]\n",
    "    \n",
    "    return a, b\n",
    "\n",
    "def getMidpeek(data):\n",
    "    density = np.histogram(data, bins=100 ,density=True)\n",
    "    \n",
    "    weight = density[0]\n",
    "    tempx = density[1][0:-1]\n",
    "\n",
    "    temp_offset = np.mean(tempx)\n",
    "    tempx = tempx - temp_offset\n",
    "    \n",
    "    # fit with a smooth line\n",
    "    z = np.polyfit (tempx, weight, 20)\n",
    "    fitfunc = np.poly1d(z)\n",
    "    \n",
    "    x = np.arange(tempx[0],tempx[-1],(tempx[-1]-tempx[0])/100)\n",
    "    y = fitfunc(x)\n",
    "    \n",
    "    plt.plot(x,y)\n",
    "    plt.plot(tempx,weight)\n",
    "    plt.show()\n",
    "    plt.savefig(\"fit_vs_ori.pdf\")\n",
    "    \n",
    "    maxid = argrelextrema(y, np.greater)\n",
    "    maxes = y[maxid]\n",
    "    a = np.sort(maxes, kind=\"quicksort\")\n",
    "\n",
    "    maxima1 = a[-1]\n",
    "    maxima2 = a[-2]\n",
    "\n",
    "    maxid1 = np.where(y == maxima1)[0]\n",
    "    maxid2 = np.where(y == maxima2)[0]\n",
    "    # maxid1, maxid2\n",
    "\n",
    "    maxtemp1 = x[maxid1]\n",
    "    maxtemp2 = x[maxid2]\n",
    "\n",
    "    midpeek = (maxtemp1[0] + maxtemp2[0]) / 2.0 + temp_offset\n",
    "    \n",
    "    return midpeek\n",
    "def index_by_value(temp, midpeek):\n",
    "    sleepidx = np.nonzero(temp < midpeek)[0]\n",
    "    awakeidx = np.nonzero(temp >= midpeek)[0]\n",
    "    return awakeidx, sleepidx\n",
    "\n",
    "def idx_to_stage(idx):\n",
    "    stages = []\n",
    "    last = idx[0]\n",
    "    i=1\n",
    "    while i < len(idx):\n",
    "        current = idx[i]\n",
    "        if (current - idx[i-1] > 1):\n",
    "            stages.append([last, idx[i-1]])\n",
    "            last = current\n",
    "        i+=1 \n",
    "    return stages\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read the meta data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "debug = 0\n",
    "# Readin the meta data\n",
    "path = '.'\n",
    "metaData = pd.read_csv(\"./mice\", index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12Otx2\n",
      "./batch3/12Otx2.Activity.txt\n",
      "./batch3/12Otx2.Temperature.txt\n",
      "56Otx2\n",
      "./batch3/56Otx2.Activity.txt\n",
      "./batch3/56Otx2.Temperature.txt\n",
      "73Otx2\n",
      "./batch3/73Otx2.Activity.txt\n",
      "./batch3/73Otx2.Temperature.txt\n",
      "84Otx2\n",
      "./batch3/84Otx2.Activity.txt\n",
      "./batch3/84Otx2.Temperature.txt\n",
      "82WT\n",
      "./batch3/82WT.Activity.txt\n",
      "./batch3/82WT.Temperature.txt\n",
      "83WT\n",
      "./batch3/83WT.Activity.txt\n",
      "./batch3/83WT.Temperature.txt\n",
      "51M\n",
      "./batch5/51M.Activity.txt\n",
      "./batch5/51M.Temperature.txt\n",
      "52M\n",
      "./batch5/52M.Activity.txt\n",
      "./batch5/52M.Temperature.txt\n",
      "54M\n",
      "./batch5/54M.Activity.txt\n",
      "./batch5/54M.Temperature.txt\n",
      "56M\n",
      "./batch5/56M.Activity.txt\n",
      "./batch5/56M.Temperature.txt\n",
      "58M\n",
      "./batch5/58M.Activity.txt\n",
      "./batch5/58M.Temperature.txt\n",
      "53\n",
      "./batch5/53.Activity.txt\n",
      "./batch5/53.Temperature.txt\n",
      "55\n",
      "./batch5/55.Activity.txt\n",
      "./batch5/55.Temperature.txt\n",
      "57\n",
      "./batch5/57.Activity.txt\n",
      "./batch5/57.Temperature.txt\n",
      "68M\n",
      "./batch6/68M.Activity.txt\n",
      "./batch6/68M.Temperature.txt\n",
      "62M\n",
      "./batch6/62M.Activity.txt\n",
      "./batch6/62M.Temperature.txt\n",
      "64M\n",
      "./batch6/64M.Activity.txt\n",
      "./batch6/64M.Temperature.txt\n",
      "61\n",
      "./batch6/61.Activity.txt\n",
      "./batch6/61.Temperature.txt\n",
      "63\n",
      "./batch6/63.Activity.txt\n",
      "./batch6/63.Temperature.txt\n",
      "65\n",
      "./batch6/65.Activity.txt\n",
      "./batch6/65.Temperature.txt\n",
      "67\n",
      "./batch6/67.Activity.txt\n",
      "./batch6/67.Temperature.txt\n"
     ]
    }
   ],
   "source": [
    "database = {}\n",
    "for mouse in metaData.index: \n",
    "    print (mouse)\n",
    "    batch = metaData.loc[mouse, 'batch']\n",
    "    act, temp = readMiceData(batch, mouse)\n",
    "    database[mouse] = [act, temp]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metaData.loc['12Otx2', 'batch']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "path = '.'\n",
    "batch = 3\n",
    "mouse = '12Otx2'\n",
    "act, temp = readMiceData(batch, mouse)\n",
    "\n",
    "# data overview\n",
    "plt.plot(temp[:,0], temp[:,1])\n",
    "plt.show()\n",
    "plt.plot(act[:,0], act[:,1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "winSize = 6\n",
    "winNum = len(temp) // 6\n",
    "tmp = temp[:,1].reshape(winNum,winSize)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tempave = np.mean(tmp, axis=1)\n",
    "sb.distplot(tempave)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(array([2.46245737e-03, 2.46245737e-03, 4.92491475e-03, 9.84982950e-03,\n",
      "       1.47747442e-02, 2.21621164e-02, 3.52952224e-02, 5.13011953e-02,\n",
      "       5.29428336e-02, 8.49547794e-02, 1.17787544e-01, 1.43643347e-01,\n",
      "       1.74424064e-01, 2.17106659e-01, 2.58968434e-01, 2.89749151e-01,\n",
      "       3.16425773e-01, 3.50079357e-01, 4.37086184e-01, 4.42011099e-01,\n",
      "       4.40369461e-01, 4.45704785e-01, 4.62121167e-01, 5.09728677e-01,\n",
      "       5.07676629e-01, 4.80589598e-01, 4.66635673e-01, 4.39959051e-01,\n",
      "       3.88657856e-01, 3.43102394e-01, 3.00830209e-01, 2.68818263e-01,\n",
      "       2.43783280e-01, 2.44604099e-01, 2.04383962e-01, 2.04383962e-01,\n",
      "       1.85915532e-01, 1.90430037e-01, 2.03563143e-01, 1.94123723e-01,\n",
      "       1.79348979e-01, 1.95354952e-01, 1.76886521e-01, 1.72782426e-01,\n",
      "       1.81401027e-01, 1.86325941e-01, 1.63753415e-01, 1.73603245e-01,\n",
      "       1.64163825e-01, 1.54724405e-01, 1.52672357e-01, 1.34614336e-01,\n",
      "       1.41591299e-01, 1.48978671e-01, 1.46926623e-01, 1.73192835e-01,\n",
      "       1.91661266e-01, 1.80990617e-01, 1.90430037e-01, 1.97407000e-01,\n",
      "       2.02331914e-01, 2.05615191e-01, 2.17927478e-01, 2.34754270e-01,\n",
      "       2.28187717e-01, 2.59789253e-01, 2.72101540e-01, 2.81540960e-01,\n",
      "       2.84003417e-01, 2.93853247e-01, 2.98367752e-01, 3.20529868e-01,\n",
      "       3.52131405e-01, 3.81270484e-01, 3.85374579e-01, 4.41600689e-01,\n",
      "       4.46115194e-01, 4.26005126e-01, 4.28057174e-01, 3.96455637e-01,\n",
      "       3.99738914e-01, 3.76755978e-01, 3.68958197e-01, 3.25044373e-01,\n",
      "       3.12321677e-01, 2.52812290e-01, 2.11771334e-01, 1.70730378e-01,\n",
      "       1.44053756e-01, 1.09168944e-01, 7.42841308e-02, 5.82781579e-02,\n",
      "       4.47346423e-02, 4.02201371e-02, 2.66766216e-02, 1.19018773e-02,\n",
      "       6.15614344e-03, 4.92491475e-03, 2.05204781e-03, 4.10409562e-04]), array([32.9745    , 33.01902833, 33.06355667, 33.108085  , 33.15261333,\n",
      "       33.19714167, 33.24167   , 33.28619833, 33.33072667, 33.375255  ,\n",
      "       33.41978333, 33.46431167, 33.50884   , 33.55336833, 33.59789667,\n",
      "       33.642425  , 33.68695333, 33.73148167, 33.77601   , 33.82053833,\n",
      "       33.86506667, 33.909595  , 33.95412333, 33.99865167, 34.04318   ,\n",
      "       34.08770833, 34.13223667, 34.176765  , 34.22129333, 34.26582167,\n",
      "       34.31035   , 34.35487833, 34.39940667, 34.443935  , 34.48846333,\n",
      "       34.53299167, 34.57752   , 34.62204833, 34.66657667, 34.711105  ,\n",
      "       34.75563333, 34.80016167, 34.84469   , 34.88921833, 34.93374667,\n",
      "       34.978275  , 35.02280333, 35.06733167, 35.11186   , 35.15638833,\n",
      "       35.20091667, 35.245445  , 35.28997333, 35.33450167, 35.37903   ,\n",
      "       35.42355833, 35.46808667, 35.512615  , 35.55714333, 35.60167167,\n",
      "       35.6462    , 35.69072833, 35.73525667, 35.779785  , 35.82431333,\n",
      "       35.86884167, 35.91337   , 35.95789833, 36.00242667, 36.046955  ,\n",
      "       36.09148333, 36.13601167, 36.18054   , 36.22506833, 36.26959667,\n",
      "       36.314125  , 36.35865333, 36.40318167, 36.44771   , 36.49223833,\n",
      "       36.53676667, 36.581295  , 36.62582333, 36.67035167, 36.71488   ,\n",
      "       36.75940833, 36.80393667, 36.848465  , 36.89299333, 36.93752167,\n",
      "       36.98205   , 37.02657833, 37.07110667, 37.115635  , 37.16016333,\n",
      "       37.20469167, 37.24922   , 37.29374833, 37.33827667, 37.382805  ,\n",
      "       37.42733333]))\n"
     ]
    }
   ],
   "source": [
    "density = np.histogram(tempave, bins=100 ,density=True)\n",
    "print (density)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f7a18249f10>]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "weight = density[0]\n",
    "tempx = density[1][0:-1]\n",
    "\n",
    "temp_offset = np.mean(tempx)\n",
    "tempx = tempx - temp_offset\n",
    "\n",
    "plt.plot(tempx, weight)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "z = np.polyfit (tempx, weight, 20)\n",
    "fitfunc = np.poly1d(z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9FBb+Oyz/tfN2PvNaFHauDsjlzZ01J99efI0UujuwWfHrb6XVFM6MSaGGxegOTyfJWkFjR59hGYSb62sn48Bj7DLPgu/vcpR5oBMv4sdmQuwMbgrczueFjVhsduft2wtIobuDnmYUGv+wePx9zIbF8JuUTapqYHeFLOgrhlef9wlm7DTM+i6miCTXHCT7WlJ68pnaf4CdVTK/0KmQQncDA+2OW7+i4hIMzRGdNgdfZaO6ZI+hOYT7qt35AV06gKXLlrvuIPNuwx6eygt+v6Zox6euO44HkkJ3A1VVjrmgJyekGJrDd+JMALqr9xmaQ7inPouN2KbNVATPJSY8xHUHCorG9K21dPpGcn3BPVC12XXH8jBS6G7gYG0VAOlTRvFwhjNFTcWmzAS0FTFglbFL8XWfb91BMg0EZ13k+oOFTuKfZz5PnT0C+4vXQIssgDESUuhuoOXQQQCiYo0dcsHHj+6QNKbqag7UdxibRbidqu3vA5Cy8NIxOd6Zs2dwp+VeTNZeqNwwJscc76TQDaa1pretjn4VAP7BRsfBJ34GGaqWXXIxSgxR2NBBcts2uvzjUdGjmLdlFFKig9BR6fSqCdAgz0eMhBS6wWpbewmytDAQ4B4PUAQmZJNoaqKg6ujpeoQ3+/v2KpaY9uM77TznPBU6QudNj6fAloBNCn1EpNANtqu6lWjaMYeeYFHdsRTrWKSgo3qvwUGEu+i32ijevZ4w1Y1/xgVjeuxzM2MpsCdhr88HLVMBnIwUusF2VbUSZ2onIHyi0VEc4hyFHtFVSrMs2iuAzwoamTOwC42C1GVjeuwFKZFUmFPwtbRDh/zUeDJS6AbbXdNGnLkTU0is0VEcwpKw+QSSoWrIq24zOo1wA6/vqOF8v/0wcTYEje3iK75mEwEJjnmG9CEZdjkZKXQD9VlsFNW1EmLvcCzH5Q5MJlRsJpmmGnbXyIVRb1fX1ktuSQ3ZFKPSlhmSYXLGfADaK2Qm0JORQjfQ/rp2EnQ9Cg3hiSf/DWPEFDeD6eaD5NXIGbq3e3tXLfNVEWZtg9SzDckwb1oKNfYYOqryDDn+eCKFbqDd1W0sMA2u45l4hrFhhorNIly3U1tTJXNSezG7XfNGbi3XRFaAyQeSjPk7mh4bTJkpGb/DBYYcfzyRQjdQXk0b5/iXQlAMRE0xOs6/DF4YTbBUUNrYZXAYYZRtFS1Ut/Rwlm8RTJ4PfsYsCWcyKbojMonurwaLzAR6IlLoBtpd3UaOudhx5mPAKkXHFeeY0yVTVbO7WsbRvdXfc2uI9bcS2ZYPKUsNzRKYOAsf7DSUybDLiUihG6Spsx9LWx0xljpIOtPoOF8XFI0Omcgc3xoZR/dSHX0W1ubX8920JpS2GV7oSdMXAVBTuMPQHO5OCt0geTVDxs8NGps8ERWfzRzfGnbLrYte6R976uiz2FkRUgYmX0hcZGie1PSZ9OJHb4088HYiUugG2V3dykJzEdo3COJnGx3nWPHZTLJWU9l4mM4+i9FpxBh7Y0cNmfEhxB7ebuj4+REmHx8a/FMJbC00NIe7k0I3SF5NG0v9SlAJOWAe0VrdYys+G7O2MZWD7KttNzqNGEOFDR3sqW3npjmRqLrdhg+3HDEQlUWqrYK61h6jo7gtKXQD2Oya8tp6Um2V7jd+fkS84+m8LFMVu+TCqFd5Y0ctvmbF1dE14Abj50eEpswhSnWSV1hkdBS3JYVugNLGLqZZCjBhd8vxcwAiUsE3iMVBdeyScXSvMWC1887uWi7MiiOkfuvg+PlCo2MBEDfV8cRoU4GsYHQ8UugGyKtpJcdUhFZmSFhgdJzhmUwQP5PZPjXsqm7FLg8YeYWPDzTQ2mPhhpxEqNzoFuPnR5gSc2gxx7C09s9gk+s6w5FCN0BeTRtn+hTDxFlusajFccVnkzhQSntPP+XN3UanEWPglW3VJERM4KwEX3Cj8XMAfCewLfN+ptir6Fn/uNFp3JIUugH2VTUxW5Wi3HX8/Ij4bHyt3SSoJlnByAuUNXWxuewwqxYmYS58zzF+Pv0yo2N9TcT8q/nYNh//jb+B1iqj47gdKfQx1jNgJbhpN356AJIXGx3nxOKzAVgQcJCdUuge79Vt1fiYFNfnJMDeNyAqHSbOMTrW18xKCOOXtm9i08Da/yeLXhxFCn2M7att51zTLuwmX0hbZnScE4vNAmViWWgDO+VOF4/WZ7Hx5q5aLp4RT6ytCao2wawb3WtKCiDQz4ew+BTeCLkVStZB6WdGR3IrUuhjbE9tG+ebdmNNXAz+IUbHOTHfCRA9jWyfakobu2jrGTA6kXCRtfvqaeuxcPOiJNj3d8eL2dcZG+o45iaF87u2c9DKBDXbjI7jVkZU6EqpS5RSRUqpUqXU/cO8f6VSaq9SKk8plauUcqMrKe7lYNl+pprq8Ju+wugoIxOfzaTeEgCZBsCDvbytmtToIM5Mi3QMtyQugshUo2MNa15SBG39YAmeDK2VRsdxKyctdKWUGXgCWA5kAauUUllHbfYZMFtrPQf4FvCss4N6ioiDXzg+mXaRsUFGKj4b/556okxdMo7uoQrqO9hZ1cpNC5NQjfuhqQCyrzc61nHNTYoAoMVvkhT6UUZyhr4QKNVal2utB4DXgCuHbqC17tL6q6sTQYBcqRhGY2cf8/u30xqYCpFpRscZmcELo8ujm6XQPdRzmyoI8DVx3fzBi6EmH5hxjdGxjislKpCIQF+q7DFS6EcZSaFPBmqGfF07+NrXKKWuVkoVAh/gOEsXR8kvP8giUwH9aRcaHWXkBicOWxZcTV5NG1ab3eBAwpmaOvt5d3cd181PIMKnH/a9CVMvGPPFoE+FUoq5SRHk90RAdyMMyDMSR4yk0Ie7zH3MGbjW+h2tdSZwFfDgsDtS6o7BMfbcpqamU0vqATr3r8NP2YiYe4XRUUYuKApiMpll20+vxUZhQ6fRiYQTvbi1Cqvdyg8it8Pj86GzDnLc/3xsbmI4uzvDHV/I/ehfGUmh1wJDVzBOAOqOt7HWej0wRSkVPcx7q7XWOVrrnJiYmFMOO95F1H5BlwrCP8XNHyg6WvISolt2YcZGbmWL0WmEk/RZbHy0JY/PQ35J7Oc/hPAk+PZnMO1io6Od1LzkCKp1rOMLGXb5ykgKfQeQrpRKVUr5ASuBNUM3UEpNVcpxw6pSah7gBxx2dtjxzG6zMaN7G2VhZ7rndLknkrIEk6WbZaH1bJdC9xjv7qjgYetvSLTXwDXPwu2fQEKO0bFGZFZCGDVIoR/tpIWutbYC3wPWAQXAG1rr/UqpO5VSdw5udi2Qr5TKw3FHzI1DLpIK4OCBLUSpdvpSLjA6yqlLdtyFelV4OVvLW5D/tOOf3a4J/uK/mG8qwXTVUzDrerd7iOhEQgJ8iYudSI8KlEIfYkSnilrrtcDao157esjnvwZ+7dxonqVt/yckAjGz3f/H2WOExEFUOvM5QEv32ZQ0djEtzs0fihInVPTBH7nMso7iaf/OtJlXGx1nVOYkRVC9L5aM1sphL/R5I3lSdIxMOLiJYp1ISrJ7PqxxUilLiG/bjQk7W8tlNG1c6u+CA++h376DqTt/yVbTPFKvf9joVKM2KyGcClsM1uZyo6O4DSn0sWDtJ7FzL+XB8zGZxum5RPJSTAOdLAttYEuZFPq4c2AN/HYqvHErlsKPeNu6lKaLn8DX19foZKM2KyGMah2Lqb0a7HI7LYxwyEWcnv6qHfjTT89kN59d8URSlgBwZUQFv6hIwW7X4/d/Tt7m4C54+w6Iy8J+/s+58l0bA/6KjxdMNzrZaZkWF8LfVRxmez90HYLQiUZHMpycoY+Bw/s+waYV4dPPNTrK6IVOgsg0cjhAS/cAJY1dRicSI9FRB6/dBEExsOp13u+cSkFjD/deMA3zOP8fsp+PCXVkvpnWCmPDuAkp9DGgKjeQr1OZOSXJ6CinJ3kJE9t2yTj6eDHQDa+uhP5OuOk1rBOiePTTYjLjQ7g02zPOZsMnpQNgb5FCByl01xvoIaZtD/t8ZxEbGmB0mtOTshRTfztnhzbKOPp48PFPoX4vXPdXiJvBmztrKW/q5t4LpnnMcFlCagZ2rWg7WGJ0FLcghe5qNVvxwUpr3Dh7OnQ4g+tLXh1RxraKw7JwtDur2gy5f4Uz7oJpF9PaPcCvPypkYUokF8+IMzqd08xKjqGOKLoaSo2O4hak0F2st+gLLNpMULoHTBEflgAx01ls3U5rj4XiRpnXxS1Z+mDN9x2P8p/3AAC/WVdIR5+VB6+aiRpHDxCdzJSYYA4SKw8XDZJCd7GB0n+Sp6cwI9kzxiyZfhnRLTuJpEOGXdzV+t/A4VK47FHwC2JXdSuvbq/hW0tSyIj3rAfCzCZFV2AiIb21RkdxC1LortTXTkhLPlv1TLITwoxO4xyZl6G0nRtC89lQ0mx0GnG0hnzY9BjMvgmmno/VZuen7+QTHxrAPRdMMzqdS6jIFCLsrVj75M4rKXRXqt6GCTu1YTkE+nnILf8TZ0NYElcH7GZTaTO9AzajE4mhdj4HZn+4+FcAPLOhggP1Hfzs8iyC/T3k7+BRQic67nSpKiswOInxpNBdSNfnARCQPN/gJE6kFGReSnrXDnys3Wwpl7N0t1KxAZIXQ2AkO6ta+f3HRazIjmf5zHijk7nMxFTHA1J1FYUGJzGeFLoLdVfvpsIeR1bKJKOjONf0yzDZB7jIbx+fFTQanUYc0dUIzUWQspT2Hgs/eHU38WEBPHzNLI+6EHq0icmZAHTUFRucxHhS6K5Uv48DOpk5iRFGJ3GupDMhMIpVoXv5vLBRptN1F5UbAdApZ/Hjt/ZwqKOPP900j7AJ43e+lpEwBUXRaQrF97CcoUuhu0pfO8E9NZSoNKbGBhudxrlMZshYzpy+7TS3d8mydO6iciP4hbC6JJh1+w9x3yWZzEkMNzqV6ylFc3AGk/pKGLB69yRdUuiu0pAPQF901rifM2NYmZfjZ+3iHp+3aPv4/2Dtj6F6q9GpvFvlRhrC5/LwulIuzZ7I7UvH6VTNo2CLn0U6NZTUefettFLoLmKp2wNAcIoHXRAdKm0ZBITzPZ/3OLPiCdi+Gjb83uhU3mtw/Pz5ugQWT4nikRtne8zj/SMRljoff2Wluni30VEMJYXuIu0Vu2jSoaSnTTE6imv4BsBdW3lu/ttM73+O/hk3QP0eo1N5rfIdHwFQH5HDn2+Zj7+P2eBEYys6fSEA3VW7DE5iLCl0V6nfywF7CnOTPOyC6FChE8mZm0Ov9qdQpTnmpO6oNzqV19lQ0sT2L9bQzQQe+PaNhAR49kXQ4ajIKfSqCQQ07TM6iqGk0F3BOkB4VxnVflPG/wyLJzFjUihxof581DI44ZOcpY+NvFfh/R+ybncp33p+B4t9CvBJXUJsmIddgB8pk4nmoHQm9nj3hVEpdFdoKsQHKwOxM41O4nImk+LKOZN5uTIMjYLBh6mEC/V3wkf3Qe5fSHznGq6NO0SSvRb/qecYncxQlthZZKpKShrajI5iGCl0F+iodIzjhSbPMzjJ2Lh2XgIddn/aA1PkDH0M2HY8B33t/NqykhRzEw+3/afjjRQPmNHzNISkzCNI9VNV4r3DLlLoLtBalku39ictI9voKGMiIz6E7Mlh7LImS6G7WHtnF+1fPMom2wysi+/B/84vUOFJjiXm4mcZHc9QUVMXANBZ6b0XRqXQXUAdyqdIJzEjIdLoKGPmuvkJbOqeDB0HoavJ6Dgeqaypi2f+9BCRtsNYz7yHBy7NwhyXCXduhO9sALNnTr41Uqa46VjwxbdRztCFs2hNdFcRDYHpBPh6z61jV8ye5LjTBeQs3QW+KGzkmj9t4Pr+t+mOyuac5Tf8602/IFnxHsDsS3PgFOK6i7HYvPPCqBS6k9laKgnUPVhjvGO45YiIID9i0x0/8toOeu+PvM6mteaZ9eV86287WBmSRzL1BJ33n45ZL8Ux+mNmkqUqKPHS6Sik0J2svnA7ACGpcw1OMvYuW5hJhT2O5pIdRkfxCFabnf9+L59frS3giqwo7vN7C6KmwvTLjY7mtoKT5xKhuigvKzI6iiGk0J2srWInNq1Iy1pgdJQxd/a0GErMUzE1yJDL6erut3LHizt5aWs13zknjdFr6zAAABqiSURBVEcnfYKppQSW/9oxOZoYVuRUxxOj7RU7DU5iDCl0J1OH8qlUk0mKizI6ypjzNZsITZ1PjO0QuwrKjI4zbrX1DHDTs9v4Z1Ej/3vVTH4yz47a9CjMWglTLzA6nlszxc/EjgmfQ3uNjmIIKXQni+4qpikw3aMXFDiRuYuWAfDBxx/JPOmjcLirn1XPbKOgroM/35LDvy1MgDXfh4BwuORho+O5P79ADgckE9NVhNULL4yOqNCVUpcopYqUUqVKqfuHef9mpdTewY/NSqnZzo/q/tpbm4jTTdi84AnR4/FPdFw78G3cy3pZRPqUNHb0cePqrVQ0d/HsbTlcOC0c/vkwHNzpGGoJ9J7bYE9HX/QMpqsKShq9b9Hokxa6UsoMPAEsB7KAVUqprKM2qwDO0VrPAh4EVjs76HhQke+YDzw8zTueEB1WYCQ6PJn7fV/jnFemws/D4I1bT/x7Du6Ezx4Em2VsMrohx5n5VuraennlhgTOrn4SHsmC9b+F6VfAzGuNjjhuBCbNZaJqobiswugoY24kTyIsBEq11uUASqnXgCuBA0c20FpvHrL9ViDBmSHHi9Zyx+16KTPPMDiJsdQVj7N/y4d8UnCIVUkdxB14DxoLITbz2I0tvfDmt6C1Enpb4dLfe90teZ19Fm57bjuHWjtZl7ObxPeeANsATFsOC26HtHO97ntyOiKmLIDN0FqeC0u9a7BgJIU+GagZ8nUtsOgE298OfDjcG0qpO4A7AJKSkkYYcfwwH8qnRYUTGelhi0KfqrRzyEg+i3se28CHTc18ZN6A2r4aLnvk2G03PeYo8/SLIfcvEJMBi74z5pGN0mexcfvfcglq2MG2qJcIyiuDrCvhwgchItnoeOOSaZJjCgRvvNtqJGPow50aDHu1Syl1Lo5Cv2+497XWq7XWOVrrnJiYmJGnHAfsdk10dwnNwdOMjuIWfMwmHl81l5r+ID7zORu951XoPWoWvJYK2PCIYzhh1auQsQI+uh9KPj12hwM9sPN5jxqWsdk13391N1Oq3+RVv/8lyGSBm/4ON7wgZX46JkTQ6j+J6K4ir5tKdySFXgskDvk6Aag7eiOl1CzgWeBKrbXXLexXUt/CFGrQXnxB9GjTJ4byhxvn8IeOc1GWHvTul/71ptbw4X1g9oWL/tdxb/U1z0DsDHjzm9B56Os72/w4/OMe2PPq2P4hnME+fKn86v0DzCz+Ew/7Potpynnw3c0w7aIxDueZ+qJmMJ0Kig951xOjIyn0HUC6UipVKeUHrATWDN1AKZUEvA3corUudn5M91desAt/ZSViioeuITpKF8+IZ/mFF7HdnkHbl0/SPzDgKPNdL0DJOlj2EwgdHKLyD4brnwdLD6z/DQA1LT28s/kAvRseB6By7SNc8fgG7n5lF79dV8iaPXX0WWwG/elGoLkUfp8Be1772ssvbC5n+vb7ucfnHZh3K6x6DfxDDArpeSYkzSXVdIiCyoNGRxlTJx1D11pblVLfA9YBZuCvWuv9Sqk7B99/GvgZEAU8OXj/tVVrneO62O6nrcKxOG3MVCn0o9197lReqbyZhdU/Y/XvfsQNEUWEH9oGCQuOGS/vCE6mLfk6Ju94jlV75rG9I5y7ze8ywbeT93yXc6XlQxaaCvn04FQ+ym/AZteETfDluvkJ3LwoibQYN1uxZ9tT0N0I7/8HTJwDsZl8UdhIz9qfcavPeuxn34fp3J/IRU8nC0vLga3QUr4Llhx9U57nUkY9/JGTk6Nzc3MNObYrvPGrW7nK+iF+P633+mlMh2Wz0Pf7mQT0NNCig3k95DbKEq4hIToUk1KUNnZR2thF8aFOIuwtfOn/Q/JDFlOy8Fes3LQCU/Ii1HXPwx+yIOUsuPFFLDY7uZWtvLytinX7HeV+x9lTuPf8qQQUvwef/y8s/Q/HGbARetsctx6mngW1uRAcS8kV7/Hc6j/wkOlJLHO/ge8Vj0qZu0JnA/w+g9WB/84dP/6d0WmcSim183gnzNI8TtDWM8CkvlJaw6cSJ2U+PLMvAVf9EWtNLm/bV/DP8j6qK9pp2HMIrSEhYgJTY4M5NzOGc6adgX9pGQs3PcLCxt9Dfxuccx/4BcK822DzH6GtBt/wRM6cEsWZU6Jo7OzjkY+L+WD9Zs7L/S4LbbtAmWDbn40r9LyXwdLtGFbqOQwvXUPrX6/nF6Z8+hPPwv+y30mZu0pIPF2+UUR3FdFnsXnNVNbSPk6wu6qV2aYqLHGXGh3FvU27GJ9pF/Nt4NuDL/VZbGgNE/yO+gc38V7Y9RzkvwVTL4TJg0NZC77tKPQdz8KFv/hq89iQAP5vYT+2ggfos2p+brmNS7PjWFD4Gzh0AOLG+Mduuw22r4akM2HSHCw2Ox8E38hVXa/TF5pGwE0vOi4IC5fpiZzB9PoKiho6mZ0YbnScMSFzuThBcWkxkaqLiDTvmzL3dAX4mo8tc4CAMMdZOQqWDZltIjwRMi+DXX+D/iGPdjcWwCvXYw6JQ9+1lZr0W/huXip2zNj3venyP8cxSj5x3F+/8A4AHnz/AD9qvoy9Wf+PgG++CxMixj6TlwlImkO6Okh+daPRUcaMFLoTHFkU2m/yHIOTeJhFd8K9eyHhqOHCM+92PFX6pxzHmfrhMnjxGjD7w63vEhybwupbc7hs8Ww22GbQsvVl+gas//r9drvjThtX2vY0hEyC6ZfzwpZKXthSxe1npzPrhp/KPeZjJCRlPj7KzuHyPKOjjBkp9NNktdkJbN6LHQVxM4yO41mUgvBhnihOOgO+8QGEJ8MHP4LH5zvGqm95GyJSADCbFD+/YgZq1vVEWxt4ePUL9AxYoa8DVp8Nr/8b2KzH7tsZmkuh/AtYcDsbytv4xT8OcH5mLPddMszUB8Jl1MTBx/69aElEKfTTVFDfSY7OpyN8BgSEGh3He6QshW99BDe/BZmXws1vDvs/1LMv/wY2kz9phz7ktme3Ynnz36EhHwrfh48fcE22AsdjGhUJV3LXy7tIjw3msVVzMZvkAuiYikihzxxMTGcBvQNu/KyCE8lF0dO0q+wgq1QJA1O8Z/4Rt6EUpF/g+DiegFDMmZewsmwDXfXP4Nv4ET3nP0Rg90HY+gRET3NMgOVMxR9hiZvNN96qxd/HxLO35RDsL//UxpxSdMYtYmntXvbVtrEwzfMXnZEz9NPUXrQBP2UjOPN8o6OI48m+Hv/+Fu42v8tb9nO4dmc2zYt/CukXwdr/B2VfOO9YXU3omu283j6Dxo5+Vt+aQ0JEoPP2L05JwMwVJJqaqCr0jiXppNBPg9aa0IYt2DA7xnWFe5p6IQRGw6R5xK56korD3ax8dgeNFz3pmN3x77dBc4lTDmUp/AiF5o3OmTz1b/OYlyR3sxgpZOYKAHzKPjY4ydiQQj8N1S09zLbu43D4LMc8JMI9+QbAnRvhmx9y1vQEnv/mQurbern++XwOLn8eTL7wyo3Q03Jah+m32tj7+evU6Uhuv+5KlmXEOie/GL3QSdT4TyOtZYPRScaEFPppyCupZpYqwzTlbKOjiJMJnegoduCMtChe/PYi2nosXP5SNYXnPAXtNY6VlUY5PW9Hn4V//8smMru305l0PlfO9co1XtxS8+RlzLQX0dBQa3QUl5NCPw1thf/ErDSRM2Ql9vFmXlIE79y1mLAJvlyxxsbO2b+Eyg3w8vWw+yVoqx7xvho7+1j55634VG8kSPWTcdYNLkwuTlXgzMswK82hnR8YHcXlpNBPQ1DdFgaUH6bEhUZHEaOQFhPMO3ctZm5SONduTuKD+LuxN+TDe3fDo9mOcj/JA0jri5u4+onNVB7u5sGsWvANhFT5ic2dpGQvpkmH4esF4+hS6KPU0j1AVl8eh8LmfPWjvBh/wgP9ePH2RXzn7DR+UL2Uhf1Psf6CNeiF34GSjx1n7cNo7R7g5y9/xsd/+xXzVBGv3z6PyYe+dKz/KX8f3Iq/ry97JiwiuXWLR614NRy5OXaU9haXscxURU3q9UZHEafJz8fET1ZM5/LZk7jvrb3c+n4H0yLP412f17F/+TimyYsxmxR2O2woaeKj/AYKCvawWj9Iom8T9AIv/dKxMMfQeWeE2zg86VyCyj/GWrkFHw++5iWFPkot+z8HIHaWjJ97ipmTw3jv7iW8vfsg7+4+yLNV5/K9inc593/+RpWO/2q7nIA6Xvd5iEAfDTe8B33tULEeWqtg+mUG/gnE8QRnXUh/2X/TmbeGaCl0cbTg2vX0qAkEJnnVwkwez8ds4oacRG7ISaSpbiL6mX/wpyk7WD/lP7HZNWcHlDN7w4Mo3yC45R2IHZyfJetKY4OLE5qVNplcewbTjzOE5ilkDH0UevoHmNO7laqIJTKntQeLmZSMOfs6shv/wd1nxvCDSYXM+eJWVGCUYx6ZWJlsa7xIiJjAfp8swjuLod9zF46WQh+Fop1fEqvaIHOF0VGEq51xJwx0OWZnfP0WiM+G2z+RKXDHGaUUPXHzMWGHg547DYAU+ij05f8DqzaRtFB+zPZ4k+ZC0mLHGHnGCrh1DQRFG51KjELwlDOwa0VP2Rajo7iMFPooTD70Twr8ZhIULv+wvcLlj8Ly38KNLzrWNRXj0pz0ZIp1At2lm4yO4jJS6Keou6GEJFsVjZNldkWvEZMBi+4Ak3csNOypZiWEk0cGIc27HatWeSAp9FNUt+1tAEJmX2FwEiHEqfDzMdEWNZcAWxc0FRodxyWk0E+RX+mHFOpEsmfMNjqKEOIUBU5ZDEBP2WaDk7iGFPqp6GkhoXMP+4OXDL9SvRDCrU2fMZtmHUpr0Uajo7iEFPop6D3wIWbs9KVdbHQUIcQozEoMJ09PI6Ah1+goLiGFfgra931Ikw4jddZSo6MIIUbB38dMY/hsovproLvZ6DhOJ4U+UloTWLeV7TqLeSmev9isEJ7KN/lMALpKPW8cXQp9pNqqCLU00RA+lwBfGT8XYrxKzl7MgDbTdGC90VGcTgp9hLqKvgTA34NnahPCG8xKjWc/aZgPbjc6itONqNCVUpcopYqUUqVKqWMmfFZKZSqltiil+pVS/+n8mMZrPvAlbTqI7LmLjI4ihDgNAb5mDgZnE9dVANYBo+M41UkLXSllBp4AlgNZwCqlVNZRm7UAPwB+5/SEbiKwfht5ajrZCRFGRxFCnK7ERfgzQGelZ03UNZIz9IVAqda6XGs9ALwGfG1WKq11o9Z6B+CR6zvZ2+uJtdTSHrsAk0kZHUcIcZqS5ywDoDLvC2ODONlICn0yUDPk69rB106ZUuoOpVSuUiq3qalpNLswRHXeZwCETz/H4CRCCGeYMS2Dg8RiqdxqdBSnGkmhD3dKeuKl0I9Da71aa52jtc6JiYkZzS4M0Vb4Jd3an+z5ckFUCE9gMikaw2YxuXMvAxab0XGcZiSFXgskDvk6AahzTRz3FNa4g2K/LCJDg4yOIoRwkoC0xcSpVvbuzzc6itOMpNB3AOlKqVSllB+wEljj2ljuo7X5EMnWSnomyt0tQniSlHnnAVCZ97nBSZznpItEa62tSqnvAesAM/BXrfV+pdSdg+8/rZSKB3KBUMCulLoXyNJad7gw+5go2vEJZyhN7IxlRkcRQjjRhEnZ9KkJULMdrTVKjf8bHk5a6ABa67XA2qNee3rI5w04hmI8Tk/JBgbwIW2OXBAVwqOYfWiLnEVG0wGKD3WRER9idKLTJk+KnoDVZie2JZeaCdMx+8vSY0J4mpCpS5iuqvkyv8LoKE4hhX4CucXVZOpydPISo6MIIVwgaOoSfJSdmn0bjI7iFFLoJ3Bg2yf4KDtJ8y4yOooQwhUSctAowpp309DeZ3Sa0yaFfhwDVju6ciM2zPilnGF0HCGEK0wIxxKZQY6pmDd31px8ezcnhX4cm0qbmWvPpzNqFvjJ/edCeCq/9GUsMR/gk2152O2jembSbUihH8e63WVkmyoIyVhmdBQhhCudcRdmpbmq+++sLxk/U5IMRwp9GH0WG4cLN+KLDXOaLDcnhEeLSEbPXslNPp+zdvMuo9OcFin0YfyzqInZtn1oZYZEeUJUCE9nPvs/8cVOZvnzNHaM34ujUujDeH9vHUt9imDSXPAf/w8bCCFOIjKV7sxrucn0KR9syTM6zahJoR+lvcfCxoJqZqpSVIrcfy6Etwi58H58lY0JO54YtxdHpdCP8vL2KrJsRfhoKyTL+LkQXiNqCnVJl3OV5UM+25ZrdJpRkUIfYsBq52+bKlgVWQrKBEly/7kQ3mTS1b8CZcL86c/ot46/edKl0I/Y/y6tf76Ujwa+weVdb8CkeRAQanQqIcQYMkckcmjWdznPtplPPnjT6DinTAodoKMe/fYd2A+Xs8VvMfqyR+GGF4xOJYQwQPLl99Nkjidj94O0dfUYHeeUSKEDbHoM7FZu6L2Pjgt/j8r5JoSNatlUIcR45zuBgfN/STo1bHnjt0anOSVS6J0NsPM5NgVdQE9gIlfNlSIXwttNPvMGSoPmcXbVEzSt+x1YB4yONCJS6JsfR9ssPHD4Ym49M4UAX7PRiYQQRlOKiJv/Sp4pi5gtD2J/YhEUfWR0qpPy7kLvakTv+Asfm89GR6Rxx9lpRicSQriJqEmp6Jve5BuWH9PUbYVXb4TqrUbHOiHvLvTNf0Rb+/m/7st46OpsJvjJ2bkQ4l+Wpkcza9n1LOv4OT0BcfDhj8Huvrczem+ht1Zh37aaNbbFzJ+3gKXp0UYnEkK4oXvOT2fulMn8d88NUL8Hdr9odKTj8tpCt314H/02xWq/W3hgxXSj4wgh3JTZpHh05Ry2BCwjT03H9ukvoLfN6FjD8spCtxasxVz8IY9arub7V51DRJCf0ZGEEG4sNiSA529fxK/0N1C9rfR/+pDRkYbldYVu7eum7a0fUmKfTNKKH7E8e6LRkYQQ48C0uBD+45breN12Hj47n2GgocDoSMfwqkK32Ox8+ux/EW2tp3j+z7h5SbrRkYQQ48jiKdGEXfoLerQ/hS//GK3da1ZGryn0+vZennzsIS5oeoHimIu59MqVRkcSQoxDK87IZn/yrczqXM9r77xtdJyv8YpCX1/cxAuPPsA9Hb+lNXYh0779F6MjCSHGsUU3/zed5ghS837LW7k1Rsf5ikcXutVm55F1B9j5wn3cp/9Cd+rFxNzxnqxCJIQ4Lco/hAkX/oQzTAWsffdFNpc2Gx0J8OBCb2jv4ydPvcJ5m/6N//B5C2v2jQT92yvgG2B0NCGEB/DJ+Sa28BT+y+917nxxBwfqOoyO5JmFvnF/JR8/+m0ebvo+mQFtcM0z+FzzZzD7GB1NCOEpfPwwX/Azptgrecb0MD/66zpqWoydbtejCt1u17z3+rOkvnEet+p/0D1jFQH35sKsG0Apo+MJITzNjGvg8sdYYC7iZesPefKZJ2ns6DUsjhrJbTdKqUuAxwAz8KzW+v+Oel8Nvr8C6AG+obXedaJ95uTk6NxcJ63bZ+mjYc86Dn72NPN7N1Pvn0rkDU/gP0UWeRZCjIHGQnpevZXA1iLaCcIakU5k8kzUtIth2sXg44/drjGZTv/EUim1U2udM9x7Jx2DUEqZgSeAC4FaYIdSao3W+sCQzZYD6YMfi4CnBn91un3bPqf+0z8SHexPTLA/wXQTWLuReN1HkJ7A7ox7mXPDAygfefpTCDFGYjMJvGs9jRv+wq4dGwlrriS7/T2C816iWwWzTp1JaNaFXHDBCghLcNmIwUgGlRcCpVrrcgCl1GvAlcDQQr8SeEE7Tve3KqXClVITtdb1zg7sP9DCXHsB/S029GFowYeP1VmQeRnnXXINcyNkHVAhhAF8A4g9724uXHYXz2+u5I6PD3Am+7hpwlYuG9iAX/4nkP9jCIqBJffC4u85PcJICn0yMPRGy1qOPfsebpvJwNcKXSl1B3AHQFJS0qlmBWDaWdfBWddhtdnJr+ugvKmLSzLjCAv0HdX+hBDCmcwmxe1LU7n1zGR8TCtQSoG1Hw7lw8Fdjo+QeJcceySFPtzPBkcPvI9kG7TWq4HV4BhDH8Gxj8vHbGJOYjhzEsNPZzdCCOESvuYh95z4+MPk+Y4PFxrJXS61QOKQrxOAulFsI4QQwoVGUug7gHSlVKpSyg9YCaw5aps1wK3K4Qyg3RXj50IIIY7vpEMuWmurUup7wDocty3+VWu9Xyl15+D7TwNrcdyyWIrjtsVvui6yEEKI4Yzo0Umt9VocpT30taeHfK6Bu50bTQghxKnwqCdFhRDCm0mhCyGEh5BCF0IIDyGFLoQQHmJEk3O55MBKNQFVBhw6GnCP2ejdh3xPjiXfk2PJ9+RYRnxPkrXWMcO9YVihG0UplXu8mcq8lXxPjiXfk2PJ9+RY7vY9kSEXIYTwEFLoQgjhIbyx0FcbHcANyffkWPI9OZZ8T47lVt8TrxtDF0IIT+WNZ+hCCOGRpNCFEMJDeF2hK6V+q5QqVErtVUq9o5Ty+hUylFLXK6X2K6XsSim3uQXLCEqpS5RSRUqpUqXU/UbncQdKqb8qpRqVUvlGZ3EHSqlEpdQXSqmCwX839xid6QivK3TgE2Cm1noWUAz8xOA87iAfuAZYb3QQIw1ZEH05kAWsUkplGZvKLTwPXGJ0CDdiBX6ktZ4OnAHc7S5/T7yu0LXWH2utrYNfbsWxupJX01oXaK2LjM7hBr5aEF1rPQAcWRDdq2mt1wMtRudwF1rreq31rsHPO4ECHGsoG87rCv0o3wI+NDqEcBvHW+xciGEppVKAucA2Y5M4jGiBi/FGKfUpMNyy2g9ord8b3OYBHD86vTyW2Ywyku+JGNli50IAKKWCgbeAe7XWHUbnAQ8tdK31BSd6Xyl1G3AZcL72khvxT/Y9EYAsdi5GSCnli6PMX9Zav210niO8bshFKXUJcB9whda6x+g8wq2MZEF04eWUUgr4C1CgtX7E6DxDeV2hA38CQoBPlFJ5SqmnT/YbPJ1S6mqlVC1wJvCBUmqd0ZmMMHix/MiC6AXAG1rr/camMp5S6lVgC5ChlKpVSt1udCaDLQFuAc4b7JA8pdQKo0OBPPovhBAewxvP0IUQwiNJoQshhIeQQhdCCA8hhS6EEB5CCl0IITyEFLoQQngIKXQhhPAQ/x+060p/oIns0AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(tempx[0],tempx[-1],(tempx[-1]-tempx[0])/100)\n",
    "y = fitfunc(x)\n",
    "plt.plot(x,y, label='fited')\n",
    "plt.plot(tempx,weight, label='orignal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([23]), array([78]))"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maxid = argrelextrema(y, np.greater)\n",
    "maxes = y[maxid]\n",
    "a = np.sort(maxes, kind=\"quicksort\")\n",
    "\n",
    "maxima1 = a[-1]\n",
    "maxima2 = a[-2]\n",
    "\n",
    "maxid1 = np.where(y == maxima1)[0]\n",
    "maxid2 = np.where(y == maxima2)[0]\n",
    "# maxid1, maxid2\n",
    "\n",
    "maxtemp1 = x[maxid1]\n",
    "maxtemp2 = x[maxid2]\n",
    "\n",
    "midpeek = (maxtemp1[0] + maxtemp2[0]) / 2.0 + temp_offset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35.20069402499999"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "getMidpeek(tempave)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([     0,      1,      2, ..., 328162, 328165, 328166]),)"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmp = temp[:,1]\n",
    "np.nonzero(tmp >= midpeek)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "tmp = temp[:,1]\n",
    "\n",
    "sleeptemp = temp[tmp < midpeek]\n",
    "awaketemp = temp[tmp >= midpeek]\n",
    "\n",
    "sleepidx = np.nonzero(tmp < midpeek)[0]\n",
    "awakeidx = np.nonzero(tmp >= midpeek)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "sleepstages = idx_to_stage(sleepidx)\n",
    "awakestages = idx_to_stage(awakeidx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([0, 651], [652, 1281])"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "awakestages[0], sleepstages[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total:  328320\n",
      "awake:  160171\n",
      "sleep:  168149\n"
     ]
    }
   ],
   "source": [
    "print(\"total: \", len(temp[:,1]))\n",
    "print(\"awake: \", len(awaketemp))\n",
    "print(\"sleep: \", len(sleeptemp))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f7a1d5545d0>"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "awaketemp = temp[awakeidx]\n",
    "sleeptemp = temp[sleepidx]\n",
    "\n",
    "sb.distplot(awaketemp[:,1])\n",
    "sb.distplot(sleeptemp[:,1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35.20069402499999"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "midpeek"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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VH5+xyp/EmUyZsxk3PrbR/gIuT7zXP7IefzdzjbuFAfzwue341pNbXC8fJrtXoHE4zyQqAPhVyMi3A5g/i2QrhgjtlYdarPt6iZqmM+lS+2Ebac9V136wpcPXNJlVH/fWVNSJKDZyiKIIngX6JSoAUHFwWl0QdsyLWt172Pnhp6TeD/ILAwDFzrCD3uZJ4PTb3b6lYd62Izh9dvj6nnrrAD774FonybLNaxxxuvhPXtqF217Y4W2jDrk9oUcrxKY5uU8UFgYAD1j6CIfbG5gVx+w3K7SjPMv67l1ahYMnBlfxDDs5xWS/WbjzKJbsaSzQ1qJ4Ci9+iQwAXk/c+Upig+4BcJ8mSryoVQGaWY4HUEwi/DsUjB+trFs7urC74RRGXfhudEbhRmBMftetB0/i8gvfVZBtNZ85h9rmdvxtlr7+w7xybTpzDnWp9vASQIMkKgCQc6o6rATzj89uw66It9+PgqEn2m88sQkiwI0TR7lan5M495VH16PpTCfq77t+YPkIBMrrH1mPE+3+P/9A7iSyCijJMk1TvXQHcCCmJTi/m+VarS3biGCFKn1nmqvmEtZVgNXJ32my+NywNwwAPuPuGIKIZ/rQwBOl5EblWRXPVyfR+Bqxk9AA4O0QjMJBc+erezHJxZOkfpSYrNbwvWcHBpkZO32p5+05TkACHEi19/c661Rz2zlsOVjYcSBufmYrvv64gyeUY+iFLYct59lqyvex05fiXHdvkEmyZBkAROQZEWkWkXLTtF+KyFER2WX8fcn02e0iUisi+0Tk2qAS7kYUTtx+eX7zYTR76EsmyJYJf65uDmzdQHLP/+bfbN3+lOv1nOsu/I37dftT2FZv3UdRnD28yrqH3fllRwa9P9nRFVRybLFzBfAsgOuyTH9YVScaf8sAQESuADAFwJXGMo+JyAi/Ekvkhe8xz2J9mXr2KNx8BYqrAET+sAwAqroOgN3rxckA5qlqp6oeBFALYJKH9MWO+eZqVA78BTsacOqsu5JGtpuFUR+c3M+b1F5ulmeWHLob2F3njsOt2GGjZ89C2nm4FdsPRStNfttU1zLoocGOzh7M2zpQvbNgZwNas5Tczb27bqw9MezzKPLSDPQ2EbkZQBmAn6pqK4BRADab5mkwpg0jItMATAOA97///R6SQfnUpdrxr/N349MTSvCH7/kTizu6wq23tIqrVz/05qD36RPu4KX2Njh7KjiMh3n+3kmvnjnUNrfhg5e+L+fnTr+Wo55GXXAab4NozfTNJ9OnsEwT2l+9VomXTFU3v99Qj5qmdjz//b/OuY5vPRWPnk7d3gSeDeADACYCaATwkDE92+6U9SdS1TmqWqqqpSUlJS6T4Y5fO00cuoLoNOp7M323xyHNjrk4N78d4s03t8HEzVJh1Pe74b0RUHABOlvT1SYPYyGYhX04ugoAqtqkqr2q2gfgSQxU8zQAGGOadTSAY96S6B/fCnERqdpJqmEHTUhHUdzq1KNSJZlkUfsJXAUAERlpensjgEwLocUApojIBSIyDsB4AFu9JTFezOeiO18tD6YZpA/CHhf2K79b73pZt2m3OvhWVTb1N628a1G5xdzWonC1Vduc/35IrjTuczmuwNjpS/HLxRWuls2we5I8durtQJuzumlmHTd2moG+CGATgA+JSIOI3AJgpojsFZE9AD4L4CcAoKoVAOYDqASwAsCtqhpuhXGI1u5z31TPL0NLfVHpS9/JgN9ByJYPC3cd7X89d9MhH7aSaQY0ZGoBI4PbweQ3H2hxvc1nN9a7XhawX0VWffyMp+1YydfMuliupixvAqvqN7NMfjrP/DMAzPCSKApOFEqlYXHz1f3IrjCriqy2HL0TmYZ+dVpIYX/Xon0SuLdPMXttHTo6e4Z9li/Ptx86iT9XNwWYsuGOnnrb9rwvbTuMt2rcX1mUGU347G4z88DRwp0NqG0u3HCDAPBWTcpTSdSrIycHhn3Mdp40nzzLj57Gsr0B951fwJN1oR9QslvqP3bqbfxxi/urs9d2H0NVo7Mrh202rqJe2d7gNkmhKtoAsGxvI+5fUY37V1T3T7Ozi31t9iZ879kyW9vI1q2Cm4D+HQdNxn7+p7347tPOb6tk0jV7bXow8wMpe+PS/qPRrcNPXtqNz/16nePtevHdp7diypzN1jPaJDle53KTg64Lvvy79fh/fyzs6FlB+u3qmoJuz25J+LtPb8EdC8uHtcO3eyXzzy/uxBd/+5ajtJ05N7wQOdTPXt7taJ1RUbTdQWf62Ojo9P8WhN8FsVaXD2nZEb1LfO+CumgemlWtHd6GkMx1TktOBYcbknefbTWG4ewLueokbi3AcinaK4BsnO4yXS4GO8lWkjGvR1XR3WsvJT29zrff09vn6kndrp4+W6Uwq3FOo/qUsJvf0uv2+p8EdnGu8Cu9VtsO6jTW7WLfzfBaL97bp/37aV+fZk1LJn/Tx2M8npUIQtEGgPXGo9g7TY/Sv2g8zn3stHX9956GU5hw53LH9wP+b5ZqgAl3Lsf+pnT9+b1Lq4bVv+fa3z94x3JH284s84M/2KvCymjt6MKEO5fjiXUHLOedcGf+NP3LvJ2Otp1LvgdtnJ4f9hw9jQl3LscaU6ssP66M8q1iwp3L++vR3WwqWz6bS53/vbx62OdRMv6O5ejs8f/qO5On+5py34+aePcb+Ov/Wg0A+NkruzE+y3E04c7lWLTrKO5ZUoXxdyyPxQDuQSjeAFCTDgAHTAN07zEe/69vsa7/3mHcLH3Tp6ac5Uazx+c3+9G8ML/VWXrjzNcNdFNb+mS7cMfRnPNkWB0ofg0ibr4B61X/b2nRg2aUx24dys1QnIX+eu6eQrZ3Is7XlUdbZ0//07sL8uzTb1Q29R+PPX2FuQqI2i5WtAGgEOLQWq1Y6ipDwawrmDgFXyB6J3K3Yh0Aenr7MHNFtaueLutS7XjSRpVHtgeCzD/+k+sOWD5tCQwEC6cxo/6EvdY6xaKs/qRlk7pcB9+Zc92DWn15FlCAL3TBoba5DU+9lX1f782SmDDHey471Dqoqi6X+1dUD8rHp946gF+v3D/o/kG5g4cN41CYC0KsA8DKyiY8trYOv1pS6Wg5geBrszdixrKqnPWU5hJJrjbR3b19mLGsCl+b7a2HxHw3vb7tU6+C+XZwq/FjC+mmxzdZNqnL9V3uX17d38w12/yD44b3IpzdUqtfpVs3qxEIJj+6AfcurcqabyvKjw+bdsOsDS5S549TZ+21vOrTwYFqVVUzHlldgx2HB6Z92U53IyGX5MMOPLEOAN1GfXS2FhNWB8tZB81Dc52gM5PfDrB7ZK+9Vto5aWS+X1wH2M6k2qpePKwWMX5xe7LIdN+d7fv3xPjmZ7b7UU5aEEX99y6EWAeA/Ab/vLmaenmJwE4OnsycVs37hj653Nndm/Vp5jhrO2ddymsdUhI0X4Wd7RqeH509/udTV28fGk+lb5C3dfbgZEfXoGc2zrxtr7Q69EQTpfrjNhsPOQXRmscPXkNX27ke181tz3b1hj6cox+KOAAMqG1ux7QhTSO7jIDw+JvDqwwAewfpLxbuBWC/BUHOIGR6feVdrw/6rKOrd9g0vw2MXFWYM9P/+uUblvOYm7LuPNyKq+5Z2f9+VdXwVk5f/d0GLM9SnQFkv7KxexL+yqPpaoSunj5cdc9KzFyxr/+z7ztsbtufnggVul/bbd1b+02zNwWeDjs/x2mb1UN2ZWsV9vKQMXtzOXzyLK66ZyV227hfEnZ/P/kUbQAwH+D1Jzpy3ljyMoD5ysr0MwJ2LwTCfOAkurugtUqLvlsE+duF989nVQUUUPwLs8Rv3rbb81DYPbdmnLZxxeU1r9c7HMox6B5Jg1a0AcAuNweFm5JyWKUAWymNc3RwIO5NYt2e3KJU5RRVES6kByrWAWDoSXVFeSPmG5dw5n0+32+b68bnfy5yPqhFvmZnqsCNs4IdT9VJr6Jmq42nnaN6EziIg/OxNdmr/gphsY1qF7+omlpBeQwE2ZpNp/L0me+3Ex2Dt5WtxZdbj79Zh231J4fta81t3od+PH7mHOasq8vas63Tnkn9FusAkJFpZvdPz+/Av7+yJ7R0fPXR3M3OaprbcldT+HSC+9l8dz0SPr/5sD8JCImb7FtVVbguv+N+5ZExY1nVsGl3v+Zt9C8n7I005i6vf7u6Bl9/fPi9jrssCoJ2ftvbF+zFfy2rxpQ5m4fNP+257c4S6rOiCADZ2C3t+Fm6zHcvoBCt7bI91FMMCvWtiuM0nVsQu0feVTrYnp3jNYweQP3YZJQPy6IMAA2tZ2137lTZeKYomnP54UR7ePlwuMV93z9l9a3WM4XJp8jiZjVOmsb29mnOPpiCaop85OTZvI0jzNW8hbiSGlqN2mjRcaRC0dKevxrMXLXaXaA+h+wqygDwd/evGXQyG3qvYGjLCHMTQzeK5SZbWIFw4c4GfPqBNVi7L3uLrNUW1TUPr9qf93OrEtirO607wYurBabvZrWfPvTGPnxq5pqsn+VqirzOooM9K5+auSZv1c5zps4TC9EaafuhwYWJ3Xk6ncv42L32B4/P1zldGIoyAAQtqif8fMmKclvkHYfSban3Hc9+j8TrjTKrfvn32DjIc647wvnq1IY658Nv5nuQzG6jgny9tA49IUdN3O/vWAYAEXlGRJpFpNw07WIRWSkiNcb/i0yf3S4itSKyT0SuDSrhg9JYiI3EVFSDlRNBn2Oj2vrJb0UUq2Ilyvlu5wrgWQDXDZk2HcBqVR0PYLXxHiJyBYApAK40lnlMREb4ltohMhnrtFndIQ/1zUHwsn/803Pb8YFfLMvZH1FDq7umoYWUuczPNciJ1+Mne2dw/vjFwnLLefwKwrnWc+V/rsCqSutWTbfM3ZZ/BpdnqrpU9t5wf/ayvRZ5IgP9FQ111mE/W8VQ4CkkywCgqusAnBwyeTKAucbruQBuME2fp6qdqnoQQC2AST6llbJYUXEcvX2KP1c3Z93574v4yFEFZXF2cNNrZ2aUubzrdbxWZzq6em11S7G/KX+35W57hb3D6BJlKCdNbXN1SbHSRmALla3OFoNPhltu7wFcpqqNAGD8v9SYPgqAuTONBmPaMCIyTUTKRKQslfJn1K2w5Tt/FGInyLeNCO+DlgKvAopz5lC4Yr7v+H0TONspMGsWqeocVS1V1dKSkhLPG87Xw6Sfv1Fz27lhl6VRuOq0aiN95ORZlNUPvZCLi2CPsvqWDls9lLqVauvMO8Zx2DKdrLnuasLjEeDnjdRCH4tW/VRFndsA0CQiIwHA+J9pv9cAYIxpvtEACvLce7an+IIwacbqnJ+53fn8aEny+w0Hsx7A1UbLmu5exU0FyqN87PSeOJRfJfRcv8/afSn8nyc2+7ORLK5+6M3+Qcqj6Jpfr/VlPVHoGK29wF2nP7ux3nKeKDcycBsAFgOYaryeCmCRafoUEblARMYBGA9gq7ck2lOdowlhUsSlJHLMRX9FhTh8KhvPROJKLp+gmhxmnpnxuna39xBE/Cu5uxuIPrnOs5pBRF4E8BkAl4hIA4C7ANwHYL6I3ALgMICvA4CqVojIfACVAHoA3KqqgY0mEeXIStnxFys+bHkTX5YBQFW/meOja3LMPwPADC+J8pvbUX8y5pc1oOLYaTz6rauyfu51zNfMSXHJHve1ZUHeyLTbrUZQvD6hnBko3mqw8wUhPhH843k78fFxF4e2fS821rXgptkbcetnP+h6He88z5/bkT9wOUhPkKLcyCARTwLXn+jwtPz9K6qxZE+jp3XYuVq57YWdHtYfXBWB3aEPyb1Xdx3DHTaeKQiSl4JM2aFWtLgM1ALgix8e6Xrb5F4iAkCheL0SSIIol4airph3rxFFfCaK8i5fxNk+YNba2kDX7/W49OWkGIG9LFcVy8baE+js6cWWAy3YcTjafbu4cdDjFaZdVg9F7bcxLGaQ3DalFZHiLhhYfLegelq1w/IeQJTZ3WmCbhngdd99uzuw++S+sFvyvGHWhqzTv/XUFrxzxDvQFeKYyEH67INrC7IdqyqWLzy8ztP63Y4ol3H3a5Weli9WWy2ev/nRvJ14aurHC5SawWJ9BRC1UkP+3jiD3XbUW0QV68mfyKtCdHOdS7tQyGYAAAf2SURBVKwDQFQUcdUsgPh3eUvRlvS9K8yCbKyrgPx0/4pqy37n840OtLHuBHryNJcsxBOKQd0k/Miv3ghmxRQZ//FquC2QKBwMAIbZa+ss58l3E+43K2vyLlse8GVe1KrDKF7MI28VnESiDUMisQrIB1FonscDiIicYgBwoCZHf+rdvcqKTKKAdPZEu5VcnMU6ABS61BvqZbKFYhqblsjs/uX7wk5CoJrb3HWi54dYB4AosboAsOqvnyjJ8h0eDa3RGsK1mDAA+MTqPkDQTSkZXiiurI4M7tvBiXUAiFK1x+YD+Z/222fxmP6Mpd6eolRN98pIFDd1qQ7c+sKOnJ9HflzgGIt5AAg7Bf558q2DYSeBiBIm3gGAF4dERK7FOgCEPE4JERVIHw/2QMQ8AHCnIEqChSGO1lbMYh0AeP4nSoZTHJUuELEOAERE5J6nzuBEpB5AG4BeAD2qWioiFwN4CcBYAPUAvqGqgQwDxQsAomS4ZwkHmwmCH1cAn1XViapaaryfDmC1qo4HsNp4HwzWARERuRZEFdBkAHON13MB3BDANgDwCoCIyAuvAUABvCEi20VkmjHtMlVtBADj/6XZFhSRaSJSJiJlqVTKYzKIiMgprwPCfFJVj4nIpQBWiki13QVVdQ6AOQBQWlrqqjDPGiAiIvc8XQGo6jHjfzOAhQAmAWgSkZEAYPxv9prIPNsPatVEREXPdQAQkfeIyPsyrwF8AUA5gMUAphqzTQWwyGsic+Hpn4jIPS9VQJcBWCjpfpDPA/CCqq4QkW0A5ovILQAOA/i692RmxwsAIiL3XAcAVT0A4CNZprcAuMZLomynoRAbISIqUrF+Epj3AIiI3It5AAg7BURE8RXvAMBKICIi12IdAIiIyL1YBwBWARERuRfvABB2AoiIYizeAYARgIjItXgHAF4DEBG5Fu8AwPM/EZFrsQ4ARETkXqwDAJ8EJiJyL+YBIOwUEBHFV7wDQNgJICKKsVgHgHGXvCfsJBARxVasA8B7L/A6oiURUXLFOgDwOQAiIvdiHQD6+sJOARFRfMU6APSyGRARkWvxDgB9DABERG4xABARJVRgAUBErhORfSJSKyLTg9hGH6uAiIhcCyQAiMgIALMAfBHAFQC+KSJX+L2dnl4GACIit4K6ApgEoFZVD6hqF4B5ACb7vZF3xLoCi4goXEGdQkcBOGJ632BM6yci00SkTETKUqmUq418+X9f7j6FREQJF9SjtJJl2qD6GlWdA2AOAJSWlrqqyzl/xDtQf9/1bhYlIkq8oK4AGgCMMb0fDeBYQNsiIiIXggoA2wCMF5FxIvJOAFMALA5oW0RE5EIgVUCq2iMitwF4HcAIAM+oakUQ2yIiIncC605TVZcBWBbU+omIyBs2pCQiSigGACKihGIAICJKKAYAIqKEEo1Ah2oikgJwKOx0hOgSACfCTkREMC8GMC8GMC/ShubD/1TVErcri0QASDoRKVPV0rDTEQXMiwHMiwHMizS/84FVQERECcUAQESUUAwA0TAn7ARECPNiAPNiAPMizdd84D0AIqKE4hUAEVFCMQAQESUUA0CBiMgIEdkpIkuM9xeLyEoRqTH+X2Sa93YRqRWRfSJybXip9p+IXCgir4hItYhUicjfJDgvfiIiFSJSLiIvisi7kpIXIvKMiDSLSLlpmuPvLiIfE5G9xmePiEi2wagiLUdePGAcI3tEZKGIXGj6zL+8UFX+FeAPwL8CeAHAEuP9TADTjdfTAdxvvL4CwG4AFwAYB6AOwIiw0+9jPswF8H3j9TsBXJjEvEB6iNSDAN5tvJ8P4B+SkhcAPg3gKgDlpmmOvzuArQD+BulRCJcD+GLY382nvPgCgPOM1/cHlRe8AigAERkN4HoAT5kmT0b6ZAjj/w2m6fNUtVNVDwKoBTCpUGkNkoj8JdI7+9MAoKpdqnoKCcwLw3kA3i0i5wH4C6RHzUtEXqjqOgAnh0x29N1FZCSAv1TVTZo+A/7BtExsZMsLVX1DVXuMt5uRHlUR8DkvGAAK4zcA/h1An2naZaraCADG/0uN6aMAHDHN12BMKwZ/BSAF4PdGddhTIvIeJDAvVPUogAcBHAbQCOC0qr6BBOaFidPvPsp4PXR6sfke0iV6wOe8YAAImIh8GUCzqm63u0iWacXSVvc8pC91Z6vqRwF0IH2pn0vR5oVRvz0Z6cv4ywG8R0S+k2+RLNOKIi9syPXdiz5PROQOAD0A/piZlGU213nBABC8TwL4qojUA5gH4GoReR5Ak3HZBuN/szF/A4AxpuVHI101UAwaADSo6hbj/StIB4Qk5sXnABxU1ZSqdgNYAOBvkcy8yHD63RswUDVinl4URGQqgC8D+LZRrQP4nBcMAAFT1dtVdbSqjgUwBcCfVfU7ABYDmGrMNhXAIuP1YgBTROQCERkHYDzSN3diT1WPAzgiIh8yJl0DoBIJzAukq34+ISJ/YbTWuAZAFZKZFxmOvrtRTdQmIp8w8vBm0zKxJiLXAfg5gK+q6lnTR/7mRdh3wJP0B+AzGGgF9D8ArAZQY/y/2DTfHUjf3d+HGLZqsMiDiQDKAOwB8CqAixKcF3cDqAZQDuA5pFt2JCIvALyI9L2PbqRLr7e4+e4ASo38qwPwKIzeDeL0lyMvapGu699l/D0eRF6wKwgiooRiFRARUUIxABARJRQDABFRQjEAEBElFAMAEVFCMQAQESUUAwARUUL9f4Ozc3VBzUiVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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xRszs2L6xPIv6riH6hsesDkVdIBAwPLKvke1Lc6m0qBFQkZNKz9AYA16tAxNtmtRtKBAw1LT0x0TXy4SJwlDaBRN7Xj/TRWPPCDu2lVsWw5LQuIu21qNPk7oNne8ZZmjMb+miowutL3MjAoe1CybmPLynkaxUF+9eW2RZDBObuDR0a1KPNh0otaFYGiSdkJHsYnl+uvarx5juwVGeOdbG5UtzePxAs2VxJDgdlGalaEt9AWhL3YZqWjwkOIQVhelWh/I7NoYGS3WRSex47EATfmPYUpljdShU5KTS3DeCzx+wOpS4pi11G3lwdwMAL9S2k5eexGP7rWt5TWVTeRaP7m+isWeEityF34lJ/S5/wPDfu86zJCeVwijWTQ9XRU4qO+u6aOn3UpGjr49oCaulLiI3iMhJEakTkbunuP0WETkiIodEZJ+IvD3yoaoJrf1eit3Wv0kvtDm0gfEBXYQUE16obaexZ4S3Lc+zOhSANz/otQsmumZN6iLiBO4FbgSqgdtEpPqCw14ANhpjNgGfBB6IdKAqaHDUx4DXR1EMJvXVRZmkJyWw91yP1aEo4Aev11OalUJ1cWwMqGcmu8hOddHQreUCoimclvo2oM4Yc9YYMwY8DNwy+QBjzKD5bUdqGqCdqlHS1u8FoNhtXWXG6TgdwiVLstl3TlvqVqtt9bDrbA9/uH1JzKxlgGBJCd3TNrrCSeqlQOOky02h636HiNwqIieAXxJsrb+FiNwR6p7Z19nZOZd4F73W/uAbIhZb6gBbl2RzqmOA/mFdZGKlH75eT4rLyY6tsbUMvyw7lf6RcV2EFEXhJPWpPubf0hI3xvzMGLMa+D3gH6e6I2PM/caYLcaYLfn5+RcXqQKCLfWM5ATSk2JzjHtLZQ7GaL+6lToGvDxxqIX3X1KKO9VldTi/Y6L2f7O21qMmnKTeBExeilYGtEx3sDHmVWCZiMTG6EycidVB0gmbyrNIcIj2q1vo+6/V4/MH+JMrl1odyluUZCUjQFOfJvVoCSep7wVWiEiViCQCO4AnJx8gIssltFODiFwCJAK61UmE+QIBOgdGKcqMvf70CSmJTtaVurVf3SJ9w2P8eNd53ruhxLI6LzNJSnCSn5GkLfUomjWpG2N8wF3As0At8D/GmBoRuVNE7gwd9gHgmIgcIjhT5sNGV6BEXOfAKH5jYrqlDrC1MptDTX26E5IFfvTGOYbG/Hz6HcusDmVaZdkpNPWN6CK1KAlrnrox5mljzEpjzDJjzJdD191njLkv9Pu/GGPWGmM2GWO2G2N2RjPoxao1NPMlVgdJJ2ypzGHMF+BYsxb3WkiDoz5++Po53rmmkNVFsTGNcSqlWSkMjfroH9HB0mjQMgE20tbvJcEh5KUnWR3KjCZ21tmrXTAL6se7ztM/Ms5nYriVDsEZMADN2q8eFbE5hUJNqbV/hMLM5JiadzyV3PQkluWnsetsN3deHdsJJl4MeMf55vOnWVmYTm3rQEzvF1vkTsYh0KT96lGhLXWbMMbQ2u+N+a6XCVcsz2NPfQ9jPi3etBB+sPMcI+N+rl9jXXndcLmcDgozk7WlHiXaUreJjoFRhsf8MTtIOlFsbEIgAMNjfg429HLZ0lyLoloc+obHeOC1s1QXZ1KaHbszoyYry07hWLMHYwyhiXMqQrSlbhPHWz1A7A+STlian4YAr9fpDvLR9r1XzzI45uOdawqtDiVspVmpjIz7tbhXFGhSt4naUFIvjuE56pMlu5yUZaewU5N6VLX1e/nh6/W8b0OJbT7w4bcrS481eyyOJP5o94tN1LYOkJXiIiXRaXUoYVtekM6rp7vweMfJTI6t5ep2dWE312P7mxj3G1YWZlgU0dwUZibhkOAuXu/ZUGx1OHFFW+o2UdvqsVVLDGBZQTr+gGHXGV1cHA2t/SMcaOhl+9JcctISrQ7noiSEBkuPtWhLPdI0qduAd9zP2c7BmB0knU5FdiopLqf2q0fJM8faSHI5uGaVPYvjFbtTON7SrytLI0yTug2cah8gYKAoBmuozyTB6WBbVY72q0fB6Y4BTncMcu2qAlIT7dmLWpKVTNfgGB0Do1aHElc0qdvAm4OkNmupA1y1Mp8znUM0dOssh0gJGMOvjraRnerichtPFy0JNVJqWrScRCRpUreB2tYBUhOdtus3BXhXdXCa3XPH2yyOJH4cbOijzePlXWuLSHDa9y1c7E5GRGfARJp9XxGLyPFWD6uKMnDYcJFGeU4qa4ozebZGk3okjPkC/Pp4G2XZKWwodVsdzrwkuZxU5qZpSz3CNKnHOGMMta0e1sTI5sFz8e61hew730un9p3O2+tnuvB4fdy4rjguVmJWl2RSozNgIkqTeoxr7hthwOuzeVIvwhh4vrbd6lBsrbV/hJdPdlBdnElVDG6AMRfrStw09Y7onrYRpEk9xk1U26suttfikslWF2VQnpOiXTDz9JWnT2AM3LQ+fhbrrC0JNla0CyZyNKnHuImZL6tieNOD2YgI764u4o26bt1Ffo52ne3mF4dbuGplvi0HzKfz26SuXTCRokk9xtW2eqjMTSU9yZ5zkSe8e10RY/4AL57osDoU2/H5A3zxyRpKs1K4aoU9FxpNJzc9iaLMZG2pR5Am9Rh3vNVDdYl9W+kTLq3IpjQrhUf3N1kdiu08uKeBE20D/N171pCYEH9v2XWlOlgaSfH3CokjA95xzncPU23jQdIJDofwwS1l7KzrolHLrYatZ2iMbzx3ircty+WGdbG/AcZcVJe4OdM5yMiYblQeCZrUY9iJttAgaRy01AE+uKUcgJ9qaz1sX3/uJIOjPr5489q4mMI4lbUlmQQM1LZpaz0SNKnHsOOhr6TVxfZeZDKhNCuFK1fk8+i+RvwBLeI0m2PN/Ty0p4Hbt1farrTuxdDB0sjSpB7Djrd4yElLpDAzyepQImbH1nJa+r28drrT6lBims8f4G8eP0puWhKfv36F1eFEVWlWClmpLo7rYGlE2HtKRZw73uqhujgzrr52v3NNITlpiTy8p5FrVhVYHU7M+txDBzna3M9t2yp46nCr1eFElYiwtiRTa8BEiCb1GPTg7gb8gWB5gO1Lc9+y242dTBX7+lI3z9a0UdcxyPKCdAuiim2NPcP8urad1UUZrIuT8ZTZrC1x86PXzzHuD+CycZGyWKD/ezGqc3AUX8BQnGW/cruzuWJ5HglO4TsvnrY6lJhjjOELTxxDEG7eWBJX39JmsrYkkzF/gLqOQatDsT1N6jGqtW8EsN/GGOFIT0rg8qW5PHm4hbOd+iae7OG9jbx6qpN3ry0kKzV+Vo5O58HdDTy4u4H6riEAHnit3tbfTGOBJvUY1dbvJcEh5KfHzyDpZFeuyCcpwcl3XqyzOpSY0dgzzJeeOs7bluVymY03v5iLvPQkXE6hpX/E6lBsT5N6jGrt91KYmYzTEZ9fv9OTEviDyyt44lAzp9oHrA7HcoGA4S9+ehgR4Wsf3GjL2vnz4RCh2J3y5jdUNXea1GOQMYaW/hFbbl93Me68ehnuFBd/9eiRRT9v/XuvnmV3fQ/3vK+a0qz463ILR7E7mdZ+LwHdiHpeNKnHII/Xx/CYP+6Tem56El+8eS2HGvv44ev1Vodjmf3ne/n6cyd5z/piPnhpmdXhWKY0K4VRX4CeoTGrQ7E1TeoxqDXUr1gch4OkF7p5YwnXrS7g68+d5Hz3kNXhLLj+kXE+99BBit3JfOX96xfNbJepFIe+obRoF8y8aFKPQa39XgCK4rylDsGFJ1++dT0uh4PPPHiAoVGf1SEtGGMMf/XoYdo8Xr5122bcKS6rQ7JUYUYSDvnt61/NTVhJXURuEJGTIlInIndPcftHReRI6OcNEdkY+VAXj9a+EXLSEkl2Oa0OZUEUuZP59x2bON7i4bMPHcTnD1gd0oL4j1fO8GxNO39z42ouqci2OhzLJTgdFGYma0t9nmZdUSoiTuBe4HqgCdgrIk8aY45POqweuNoY0ysiNwL3A5dFI+DFoLXfG/f96Re6bk0h/3DLOv7+iWPc82QNX7plHY44nfkD8NrpTr72zEnWl7pJcTl1bnZIiTuFE20ejDGLuitqPsJpqW8D6owxZ40xY8DDwC2TDzDGvGGM6Q1d3AUs3tGeeRoc9dE9NLYo+tMv9LHLl3Dn1ct4cHcDn3v4IN7x+Kyvfb57iM8+dJD8jCTef0mpJq9JirOSGRrz0+4ZtToU2wonqZcCjZMuN4Wum84fAb+a6gYRuUNE9onIvs5OrdI3lZOhmtKLraU+4a9vWMXdN67mqSOtfPSB3XQMxFf/qsc7zh/91z6MCX6IJSUsji62cJWEGjO6vd3chZPUp2pGTDmRVETeQTCp//VUtxtj7jfGbDHGbMnPj6+9FiNloob6Yk3qIkJmsovbtlVwuLGPq7/6Mn/96BF+suu87bsofP4Adz14kHNdQ9z3B5eSG6erheej2J2MoLXV5yOcKo1NQPmky2VAy4UHicgG4AHgRmNMd2TCW3yOt3pIcTkXxUyImZL0+lI3hRlJPHagiUf2NXK4qc/227l96Ze1vHqqk39+/3q2L8t9s96J+q0kl5Pc9ESONWtLfa7CSep7gRUiUgU0AzuAj0w+QEQqgMeBjxljTkU8ykXkeIuH4qxk7WcFCjKTueOqZbxxposXT3TwrRdO0zkwyqffsdxWqy4f3N3A7vpufn6ohSuW5RIwM3+gLXbF7hRtqc/DrEndGOMTkbuAZwEn8ANjTI2I3Bm6/T7gHiAX+G4oGfmMMVuiF3Z88vkDnGgbYGtljtWhxAynQ7hyRT6bK7J58UQHj+xt5JG9jdy8qYQ7r15mi23e6joG+cXhFlYVZnDj+mKrw4l5JVkpHG3up294bFFUqoy0sDbJMMY8DTx9wXX3Tfr9j4E/jmxoi0991xCjvsCiWHR0sdKTErh5Ywn/+qGNPPBaPQ/taeDxA828c00hn7pmKZcuic0PwlPtAzy45zz5GUl8eGv5oivUNRcloT0Ejrd4eNvyPIujsR9dURpDjob6Ee3UtbDQSrJSuOd91bxx97V8/p0r2He+hw/8x2+49buv88sjrTG1cKnD4+UTP9yLy+ng9u2Vi2Yx2XxNzIA5pjNg5kS3s4shR5v7SXE5yc/QWRHTmdwXXZCRzOevW8n+hl6ONPXxmQcPUJqVwieuqOTDW8vJSLZusHlo1McnfrSX3uExPnlFlXYjXIS0pASK3cnarz5HmtRjyNGmftaWZOpX9IuQmOBg+9JcLqvK4USrh511XXzpl7V847lTXLkij+1Lc/nE26sWJJaJDxx/wPDfu85R1zHIxy6vpES/eV20tSWZmtTnSJN6jPAHDDUtHj68tXz2g9VbOESoLnFTXeKmsWeYl0528NzxdnbWdTHmD/CH2ytJSYx+94cxhicPN3OqfZBbN5Wyqij2B3Jj0doSNy+e6GB4zEdqoqapi6H/WzHiTOcgI+N+NpS58Y7HTr+wHZXnpPKH2ytp7Bnm+dp2/ulXJ/j2i3Vct6aArZU5b34T+shlFRF/7JdOdrD3XC/XrMxna1VsDt7awdqSTAIGalsHuHSJFju7GDpQGiOONgUHhTaUuS2OJH6U56TyiSuq+NOrlpKXnsTPD7Vw3ytnaI5SFcDX67p4vraDzeVZXF9dGJXHWCzWlgbfB8d1sPSiaVKPEUeb+0lNdFKVl251KHFnSW4af3JlFR/aUkbf8DjffamOXxxuweMdj9hjPLi7gV8ebWVtSSbvv6RMF4/NU4k7maxUl/arz4Em9RhxtLmfdSXuuN1o2moiwqbybP7snSu5bGkOu852c903XuEXh1sw89gT0xjD/a+e4W9/dpSVhel8eGu5PocRICKsK3FrUp8DTeoxwOcPUNPSz7pS7XqJtpREJzdvLOXT1yynKDOZzz50kE/8aC+NPcMXfV+BgOFLv6zlK0+f4D0bivmDy5aQ4NC3VKSsLcnkZNsA4zG09sAO9BUYA850DuEdD2h/+gIqzU7hic9cwT3vrWZPfQ/X/esrfPWZEwyE2SXT0D3Mbf+5i+/vrOfjb6vk2zs2k+DUt1MkVZdkMuYPcLp90OpQbEVnv8SAI019ANpSX2CP7G0k2eXks9eu4NmaNr778hl+9BM7FF4AAA/BSURBVMY5tlXl8JVb1085v7xrcJSf7mvi2y+exiHCVz+wgQ9u0T70aJh4P9S09FNdkmlxNPahST0GHG3uJy3RydK8NKtDWZTcKS4+tKWcty3L5cUTHbxyspMrv/oS60oyWVvqpsSdTM/QOA09Q7xyqpNxv+GaVfl8+db1WtIhiqpy00hNdFLT4uGDVgdjI5rUY8Chxj42lGXF9Z6cdlCWHZzf3js0htfnZ9+5Xp463ILH6yM9KYH8jCRu3x4sQbDCBtUh7c7hENYUZ+ouSBdJk7rFvON+jrd4uOOqpVaHokKy0xLfXJhkjGHUF9BiXBbZUObm4T2N+PwBHbMIk/4vWaympR9fwLCpPMvqUNQUREQTuoU2lWcxMu7nZPuA1aHYhiZ1ix1sCA6SbqrQpK7UhS6pCJYImHifqNlp94vFDjb2UZadQkGGboxhB7oN3cIqy04hNy2RQ419/MHlS6wOxxa0pW6xQw192vWi1DSCK4GzONjQa3UotqEtdQt1eLw0943wyQWq963Cpy3y2LG5IosXTnTQPzKOO8W6jU/sQlvqFjrYGOwn3Kz96UpNa1N5sF99YpGempm21C3y4O4GnjnWhlOEo039nGjV0X2lprKh3I1IcLD0yhX5VocT87SlbqHG3mGKs5Jx6fxbpaaVmexieX46hxq1pR4ObalbxB8wNPeO6K4uSk3hwjGNzGQXu85285Nd5/mozoKZkTYRLdLaP8KYP8CS3FSrQ1Eq5pXnpDI85qdnaMzqUGKeJnWLnOsaAqBSi3gpNauJxs+57ouve7/YaFK3SH33MLlpiWQm6xQtpWaTn5FEaqLzzcaQmp4mdQsEAoZzXUPaSlcqTA4RKnPTqO/WpD4bTeoWqOscZGTcT1WuJnWlwlWZl0bP0Bht/V6rQ4lpmtQtsLu+B9D+dKUuxkQjaM+5HosjiW2a1C2wp76HzOQEslO1P12pcBW5k0lKcLD7bLfVocQ0TeoLzBjDnvpuKvPSdF9LpS6C0yEsyU1lT7221GeiSX2BNfaM0O4ZpUq7XpS6aFW5aZzuGKR7cNTqUGJWWEldRG4QkZMiUicid09x+2oR+Y2IjIrIX0Q+zPixqz741bFSB0mVumgT41B7z2kp3unMmtRFxAncC9wIVAO3iUj1BYf1AJ8Dvh7xCOPMztNd5GckUZCRZHUoStlOaXYKyS4Hu7RffVrhtNS3AXXGmLPGmDHgYeCWyQcYYzqMMXuB8SjEGDcCAcPOui6uXJGn/elKzUGCw8HWyhx21nVZHUrMCieplwKNky43ha67aCJyh4jsE5F9nZ2dc7kLWzve6qFnaIyrtHyoUnN29cp86joGae4bsTqUmBROUp+qSWnm8mDGmPuNMVuMMVvy8xdfYnv1dPCD7IrleRZHopR9Xb0ymDtePbX4GobhCCepNwHlky6XAS3RCSe+vXqqk+riTPK1P12pOVtekE6xO5lXTmpSn0o4SX0vsEJEqkQkEdgBPBndsOLP0KiP/ed7uXKlttKVmg8R4aoV+bx+pgufP2B1ODFn1qRujPEBdwHPArXA/xhjakTkThG5E0BEikSkCfhz4O9EpElEMqMZuN3sru9m3G+0P12pCLh6VT4DXp/uhjSFsHY+MsY8DTx9wXX3Tfq9jWC3jJrGq6e6SHY5dKcjpSLgimV5OAReOdXJlsocq8OJKbqidAEYY3j5ZAeXVeWS7HJaHY5StudOdbG5IlsHS6egSX0BnGof5Fz3MO9aW2h1KErFjatX5nOkuZ8Oj5binUyT+gJ45lgbInB9tSZ1pSLlxnVFGAPP1rRZHUpM0aS+AJ6paePSimwKMpKtDkWpuLGiMIPlBek8fVST+mSa1KOsoXuY2lYPN6wrsjoUpeLOTeuK2F3fTZdWbXyTJvUom/hq+O61mtSVirQb1xcTMPBcTbvVocQMTepR9kxNG9XFmZTnpFodilJxZ3VRBlV5afzqWKvVocQMTepR1O7xcqChV7telIoSEeHGdUW8caab3qExq8OJCWEtPlJz88TBZowBY+DB3Q1Wh6NUXLppfTHfffkMvzrWxkcuq7A6HMtpSz1KjDH8dH8TFTmpWsBLqShaW5LJysJ0HtnXOPvBi4C21KPkYGMfdR2D3Lp5TqXnlVLTmOpb74qCDH55tJXaVg9rihd32SltqUfJT/c1kexysL7UbXUoSsW9zeVZJDodPLJXW+ua1KNgZMzPU4dbuGl9sdZ6UWoBpCYlcMO6Ih4/0IR33G91OJbSpB4Fz9S0MjDq44OXls9+sFIqInZsLcfj9S366Y2a1CPMGMOP3jjPktxULqvSkqBKLZTLl+ayJDeVn+xa3DPNNKlH2O76Hg439vHHVy7F4Zhqe1elVDQ4HMLt2yvZd76Xved6rA7HMprUI+x7r5whNy2RD16qe4YotdB2bCsnJy2R775UZ3UoltGkHkEn2jy8dLKTj7+tUgdIlbJAamICn7yikpdOdlLT0m91OJbQpB5B979yltREJx/bvsTqUJRatD62vZL0pAS++/IZq0OxhCb1CKnrGODnh1vYsbWCrNREq8NRatFyp7j42PYlPH20lVPtA1aHs+A0qUfIPz5VS2qik8+8Y5nVoSi16P3JlUvJSErgH35RgzHG6nAWlJYJiICXTnTwyqlO/u49a8hN1zovSlnhwvIBV6/M5xdHWvm7J47x5VvXWxTVwtOkPk9jvgB/+ehh8tITSUxwaDVGpWLEtqpc9pzr4emjrfz9e6sXzeQF7X6Zp/teOUPX4Bg3rS8mwaH/nUrFCqdDeO+GEnqHx7l3EU1x1Cw0D/vP9/DNF06zoczNqsIMq8NRSl1gWX46m8uzuPelOnaf7bY6nAWhSX2O+kfG+dxDhyjJSub3NpUioqtHlYpFN28soSInlc8/cmhR7I6kSX0O/AHDXz16mHaPl2/t2Lxo+uqUsqMkl5Nv33YJXYOj/OWjR/AH4ns2jCb1i2SM4Qs/O8qzNe387U1r2FyRbXVISqlZrC9z84Wb1vB8bTv3/PxYXE9z1NkvF8EYwz/96gQP723ks9cu55Nvr7I6JKVUmD5+RRWtHi/fe+UsWaku/vLdq60OKSo0qYfJO+7nCz87xmMHmrh9+xL+/PqVVoeklLpId9+wGs+Ij3tfOsOYL8DdN67BGWfVVDWph6G1f4RP/fgAhxr7+F/XreB/XbdCB0aVsiER4Uu/tw6XU/jP1+o52T7It3dsxp3qsjq0iNGkPoNxf4Afvl7PN58/jQE+elkFhZnJPKz7ICplW06H8H9vWcea4kzu+fkxbvzmq/z9e6u5YV1RXDTWxKoBgy1btph9+/ZZ8tizGRr18fjBZn64s56zXUNct7qA//O+teys67I6NKVUBK0pzuBvf3aM2lYPb1+ex6evWcb2ZbkxndxFZL8xZst0t4fVUheRG4BvAk7gAWPMP19wu4RuvwkYBj5ujDkw56gt0Ds0xs66Ll480cHzte0MeH1sKHPz/du3cN2awuBBi2dRmlKLwuaKbH5x1xX8eNd5vvnCaT7ywG6WF6Rz6+ZSrl6ZT3Vxpu12MJs1qYuIE7gXuB5oAvaKyJPGmOOTDrsRWBH6uQz4j9C/C8YYgz9gCBgIvPm7IRCA8UCAQa8Pj3ccz0jw3+7BURp7RzjfPcSxZg/NfSMAZKe6eFd1ER+9vILN5Vkx/YmtlJq/BKeDj19RxY5tFTx1pJWf7D7P1549ydeePYk7xcWa4gxWF2VS7E4mNz2J3PRE8tOTyEp1kZjgwOVwkOAUXE4HLqfD8oHXWbtfRGQ78EVjzLtDl/8GwBjzT5OO+R7wsjHmodDlk8A1xphpt/Wea/fLM8fa+LNHDgUTtgkm8bkuJkhMcFCWncKa4kzWl7rZWplNbesADk3kSi1qA95x8jOS2FPfw4m2AU61DzA85g/rb0XA5XAwkUbe/Bd58/Ifv72KP3/XqjnFFonul1Jg8shgE29thU91TCnwO0ldRO4A7ghdHAwlf0udBl6a+qY8YDF0out5xhc9Txv436GfMEx1njNurRZOUp+q2Xph0zicYzDG3A/cH8ZjWk5E9s30aRgv9Dzji55nfJnLeYZTJqAJKJ90uQxomcMxSimloiycpL4XWCEiVSKSCOwAnrzgmCeBP5Sgy4H+mfrTlVJKRces3S/GGJ+I3AU8S3BK4w+MMTUicmfo9vuApwlOZ6wjOKXxE9ELecHYopsoAvQ844ueZ3y56PO0bPGRUkqpyNPSu0opFUc0qSulVBxZ9EldRJJFZI+IHBaRGhH5h9D1/ygiR0TkkIg8JyIlVsc6H9Od56Tb/0JEjIjkWRVjJMzwfH5RRJpDz+chEbnJ6ljnY6bnU0Q+KyInQ9d/1co452uG5/ORSc/lORE5ZHWs8zHDeW4SkV2h89wnIttmvTNjzKL+ITjHPj30uwvYDVwOZE465nPAfVbHGo3zDF0uJzgQfh7IszrWKD2fXwT+wur4FuA83wE8DySFbiuwOtZonOcFx3wDuMfqWKP0fD4H3Bi6/iaCK/dnvK9F31I3QYOhi67QjzHGeCYdlsYUi6nsZLrzDF3+N+CvsPk5wqznGTdmOM9PAf9sjBkNHddhUYgRMdvzGSom+CHgIQvCi5gZztMAmaHr3YSx/mfRJ3UIFi0LfX3rAH5tjNkduv7LItIIfBS4x8oYI2Gq8xSRm4FmY8xhi8OLmOmeT+CuUJfaD0TE9pvLTnOeK4ErRWS3iLwiIlutjXL+Zng+Aa4E2o0xp62JLnKmOc/PA18L5aGvA38z2/1oUgeMMX5jzCaCK2G3ici60PVfMMaUAz8B7rIyxkiY4jw3AF8gDj6wJpvm+fwPYBmwiWBNom9YGGJETHOeCUA2wa/ufwn8j9i81Oh078+Q27B5K33CNOf5KeDPQnnoz4Dvz3Y/mtQnMcb0AS8DN1xw04PABxY8oCiZdJ63AFXAYRE5R/DFdEBEiqyLLnImP5/GmPbQmyYA/Ccw+4CTTVzwum0CHg99nd8DBAgWhbK9C9+fIpIAvB94xMKwIu6C87wdeDx0008J43W76JO6iOSLSFbo9xTgncAJEVkx6bCbgRNWxBcp05znQWNMgTGm0hhTSTAhXGKMabMw1HmZ4fksnnTYrcAxK+KLlOnOE3gCuDZ0/UogERtXM5zhPJn43RjTZFV8kTLDebYAV4cOu5ZgYdkZ6R6lUAz8lwQ3A3EA/2OMeUpEHhORVQRbOueBO60MMgKmPE+LY4qG6Z7P/xaRTQQHns4Bf2phjJEw3XkmAj8QkWPAGHC7CU2dsKmZXrc7iJOuF6Z/PvuAb4a+lXj5benyaWmZAKWUiiOLvvtFKaXiiSZ1pZSKI5rUlVIqjmhSV0qpOKJJXSml4ogmdaWUiiOa1JVSKo78f1pDR6+pa6OmAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "path = '.'\n",
    "batch = 3\n",
    "mouse = '12Otx2'\n",
    "act, temp = readMiceData(batch, mouse)\n",
    "\n",
    "# data overview\n",
    "plt.plot(temp[:,0], temp[:,1])\n",
    "plt.show()\n",
    "plt.plot(act[:,0], act[:,1])\n",
    "plt.show()\n",
    "\n",
    "winSize = 6\n",
    "winNum = len(temp) // 6\n",
    "tmp = temp[:,1].reshape(winNum,winSize)\n",
    "\n",
    "tempave = np.mean(tmp, axis=1)\n",
    "sb.distplot(tempave)\n",
    "plt.show()\n",
    "\n",
    "midpeek = getMidpeek(tempave)\n",
    "\n",
    "awakeidx, sleepidx = index_by_value(temp[:,1], midpeek)\n",
    "\n",
    "sleeptemp = temp[sleepidx]\n",
    "awaketemp = temp[awakeidx]\n",
    "sb.distplot(sleeptemp[:,1])\n",
    "sb.distplot(awaketemp[:,1])\n",
    "plt.show()\n",
    "\n",
    "awakestages = idx_to_stage(awakeidx)\n",
    "sleepstages = idx_to_stage(sleepidx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.7.6 64-bit ('.anaconda3': virtualenv)",
   "language": "python",
   "name": "python37664bitanaconda3virtualenv4d78c01da4304e74ba108b15727ee1f2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
